<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Impute Missing Values in a Predictive Context</dc:title>
  <dc:title>R package imputeMissings version 0.0.4</dc:title>
  <dc:description>Compute missing values on a training data set and impute them on a new data set. Current available options are median/mode and random forest.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Imports: randomForest,stats</dc:relation>
  <dc:creator>Michel Ballings &lt;michel.ballings@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Matthijs Meire [aut],
  Michel Ballings [aut, cre],
  Dirk Van den Poel [aut]</dc:contributor>
  <dc:rights>GPL (&gt;= 2)</dc:rights>
  <dc:date>2024-08-30</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=imputeMissings</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.imputeMissings</dc:identifier>
</oai_dc:dc>